DocumentCode :
2609509
Title :
Morphological classification of blood leucocytes by microscope images
Author :
Piuri, Vincenzo ; Scotti, Fabio
Author_Institution :
Dept. of Inf. Technol., Milan Univ., Crema, Italy
fYear :
2004
fDate :
14-16 July 2004
Firstpage :
103
Lastpage :
108
Abstract :
The classification and the count of white blood cells in microscopy images allows the in vivo assessment of a wide range of important hematic pathologies (i.e., from presence of infections to leukemia). Nowadays, the morphological cell classification is typically made by experienced operators. Such a procedure presents undesirable drawbacks: slowness and it presents a not standardized accuracy since it depends on the operator´s capabilities and tiredness. Only few attempts of partial/full automated systems based on image-processing systems are present in literature and they are still at prototype stage. This paper presents a methodology to achieve an automated detection and classification of leucocytes by microscope color images. The proposed system firstly individuates in the blood image the leucocytes from the others blood cells, then it extracts morphological indexes and finally it classifies the leucocytes by a neural classifier in Basophil, Eosinophil, Lymphocyte, Monocyte and Neutrophil.
Keywords :
automatic testing; blood; feedforward neural nets; image classification; image colour analysis; medical image processing; microscopy; Basophil; Eosinophil; Lymphocyte; Monocyte; Neutrophil; automated systems; blood cells; blood image; blood leucocytes; hematic pathologies; image-processing systems; leukemia; microscope color images; microscopy image; morphological cell classification; neural classifier; vivo assessment; white blood cells; Cells (biology); Image analysis; In vivo; Information technology; Microscopy; Morphology; Pathology; Performance analysis; Prototypes; White blood cells;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Measurement Systems and Applications, 2004. CIMSA. 2004 IEEE International Conference on
Print_ISBN :
0-7803-8341-9
Type :
conf
DOI :
10.1109/CIMSA.2004.1397242
Filename :
1397242
Link To Document :
بازگشت